In practical work, remote sensing image registration is usually carried out manually, by using ground control points, or through observation of the human eye, which is time-consuming, laborious, and inefficient. The existing automatic registration algorithm cannot meet the requirements of multi-source remote sensing image registration in accuracy, stability, efficiency, and adaptability. Many mature algorithms are dependent on the single-mode properties of images [1]}, [2]}, [3]}, [4]}, [5]}. However, multi-source remote sensing image registration is a more complex problem in which image pairs are generally obtained from different sensors, times, and viewpoints. Thus, differences between the imaging principle, resolution, condition, and many other factors can cause a multi-source remote sensing image pair to contain changes in scale, blur, rotation, geometric and radiance distortion, content details, and noise, etc, which invalidate the algorithms.
